Detect tumors in brain images
Assess diabetes risk based on health metrics
Classify health symptoms to suggest possible diagnoses
Conduct health diagnostics using images
Explore and analyze medical data through various tools
Evaluate your diabetes risk with input data
Predict heart disease risk using health data
Segment teeth in X-rays
Predict eye conditions from OCT images
Describe a medical image in text
Classify and assess severity of lung conditions from chest X-rays
Predict pediatric pneumonia from chest X-rays
Predict breast cancer from FNA images
Brain Tumor Segmentation is a medical imaging tool designed to detect and analyze tumors in brain images. It uses advanced AI algorithms to identify abnormalities and provide detailed insights, aiding in diagnosis, treatment planning, and monitoring. This technology is particularly useful for neurologists, radiologists, and oncologists to process MRI or CT scans efficiently.
• Automatic tumor detection: Quickly identifies tumor regions in brain images.
• Multi-modal support: Works with various imaging modalities like MRI (T1, T2, FLAIR) and CT scans.
• Quantitative analysis: Provides metrics such as tumor size, volume, and growth patterns.
• Advanced visualization: Generates clear and detailed segmentation maps for better understanding.
• User-friendly interface: Designed for ease of use, even for non-experts.
What imaging modalities does Brain Tumor Segmentation support?
The tool supports MRI (T1, T2, FLAIR) and CT scans. Support for other modalities may vary.
How accurate is the segmentation process?
The accuracy depends on image quality and modality. MRI scans generally yield higher accuracy due to better tissue contrast.
Can non-experts use Brain Tumor Segmentation?
Yes, the tool is designed with a user-friendly interface, making it accessible to non-experts while still providing advanced functionality.